From 8e56b0e634c0f8681dde2c85a5afa96d543960dc Mon Sep 17 00:00:00 2001
From: Christopher Rhodes <christopher.rhodes@embl.de>
Date: Tue, 16 Jul 2024 20:58:44 +0200
Subject: [PATCH] Need to standardize whether binary_mask is (Y, X, 1, 1) or
(Y, X)
---
model_server/base/roiset.py | 14 +++++++++++---
1 file changed, 11 insertions(+), 3 deletions(-)
diff --git a/model_server/base/roiset.py b/model_server/base/roiset.py
index 6afa4b1a..f0af11a7 100644
--- a/model_server/base/roiset.py
+++ b/model_server/base/roiset.py
@@ -172,8 +172,15 @@ def _make_df_from_object_ids(acc_raw, acc_obj_ids, expand_box_by) -> pd.DataFram
df = _df_insert_slices(df, acc_raw.shape_dict, expand_box_by)
# TODO: make this contingent on whether seg is included
+ def _make_binary_mask(r):
+ acc = InMemoryDataAccessor(acc_obj_ids.data == r.label)
+ acc.get_mono(0, mip=True)
+ cropped = acc.crop_hw((r.y0, r.x0, (r.y1 - r.y0), (r.x1 - r.x0))).data
+ return cropped
+
df['binary_mask'] = df.apply(
- lambda r: (acc_obj_ids.data == r.label).max(axis=-1)[r.y0: r.y1, r.x0: r.x1, 0],
+ # lambda r: (acc_obj_ids.data == r.label).max(axis=-1)[r.y0: r.y1, r.x0: r.x1, 0],
+ _make_binary_mask,
axis=1,
result_type='reduce',
)
@@ -327,7 +334,7 @@ class RoiSet(object):
:param params: optional arguments that influence the definition and representation of ROIs
:return: object identities map
"""
- return __class__.from_object_ids(acc_raw, _get_label_ids(acc_seg, allow_3d=allow_3d, connect_3d=connect_3d), params)
+ return RoiSet.from_object_ids(acc_raw, _get_label_ids(acc_seg, allow_3d=allow_3d, connect_3d=connect_3d), params)
# TODO: generate overlapping RoiSet from multiple masks
@@ -519,13 +526,14 @@ class RoiSet(object):
patch[roi.relative_slice][:, :, 0, 0] = roi.binary_mask * 255
else:
patch = np.zeros((roi.y1 - roi.y0, roi.x1 - roi.x0, 1, 1), dtype='uint8')
- patch[:, :, 0, 0] = roi.binary_mask * 255
+ patch = roi.binary_mask * 255
if pad_to:
patch = pad(patch, pad_to)
return patch
dfe = self._df.copy()
+ # TODO: can just pass function handle
dfe['patch_mask'] = dfe.apply(lambda r: _make_patch_mask(r), axis=1)
return dfe
--
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